Updates of sea ice snow melt onset for marine mammals studies

in the Chukchi Sea and adjoining waters



Nikita Platonov

A. N. Severtsov Institute of Ecology and Evolution of Russian Academy of Sciences, Moscow (󠀠IEE RAS󠀠)


The 26th Meeting of the Marine Mammals Working Group
Anchorage, 02 February 2020
pdf version

Urgency

[[@Mordvintsev2011, Fig.6]]{.adopted}

(Mordvintsev et al., 2011: Fig.6)

Methods

Snowmelt onset estimates

Timeseries for melt onset and freeze onset detection. Adopted [[@Belchansky2004_RSE, Fig. 4, fragment]]{.adopted}.

Timeseries for melt onset and freeze onset detection. Adopted (Belchansky et al., 2004, Fig. 4, fragment).

All considered methods for estimating snowmelt onset dates are based on passive microwave data. Timeseries are generated from channels combination (difference). Onset is argument of sharp changing of timeseries variability or crossing threshold value.

Tendency and segmentation

Example for dummy values

Example for dummy values

Blue: linear regression.

Green: Non-parametric segmentation of a time series using the penalized contrast method (Lavielle, 1999). Non-parametric estimation the best number of segments (Lavielle, 2005).

Results

Sea ice snow melt onset

Melt onset methods comparison: PMW (Markus and Miller, 2019; Markus et al., 2009), NSIDC (Anderson et al., 2019), AHRA (Drobot and Anderson, 2001) reproduction (Belchansky et al., 2004), MDSDA (Belchansky et al., 2004), “Tentative” (unpublished)

NSIDC snow melt onset [@AHRA_v4]

NSIDC snow melt onset (Anderson et al., 2019)

Linear slope: -0.4±0.18 d yr-1 (S=0.98)
Period Length Mean, DOY St.dev, days Julian
1988-2001 14 131.18 9.01 May11
2002-2009 8 117.82 5.89 Apr28
2010-2017 8 124.10 4.77 May04
AHRA algorithm [@DrobotAnderson2001_AHRA] updated reproduction [@Belchansky2004_RSE]

AHRA algorithm (Drobot and Anderson, 2001) updated reproduction (Belchansky et al., 2004)

Linear slope: -0.5±0.15 d yr-1 (S=0.996)
Period Length Mean, DOY St.dev, days Julian
1988-2001 14 133.61 8.66 May14
2002-2019 18 123.47 6.48 May03
MDSDA [@Belchansky2004_RSE] snow melt onset without adaptive smoothing

MDSDA (Belchansky et al., 2004) snow melt onset without adaptive smoothing

Linear slope: -0.2±0.11 d yr-1 (S=0.95)
Period Length Mean, DOY St.dev, days Julian
1988-2001 14 148.02 6.53 May28
2002-2019 18 142.67 4.35 May23
«Tentative» algorithm (Platonov 2007, *unpublished*)

«Tentative» algorithm (Platonov 2007, unpublished)

Linear slope: -0.2±0.09 d yr-1 (S=0.96)
Period Length Mean, DOY St.dev, days Julian
1989-2013 25 144.29 3.65 May24
2014-2019 6 139.55 7.24 May20

Summary

Finalizing

  • Google trends, variability, and periodicity of polar keywords

    []{style="display: none;"}

    []{style="display: none;"}

Supplemental information

Speaker

  • Nikita Platonov ✉

Affiliation

  • A.N.Severtsov Institute of Ecology and Evolution of Russian Academy of Sciences (IEE RAS)

  • Permanent Expedition of Russian Academy of Sciences

  • “Polar Bear Research in the Russian Arctic” Program

Co-working

  • Ilia Mordvintsev (IEE RAS)

  • David Douglas (USGS, AK, Juneau), Area V Activity 02.05-7105 and friendship

Acknowledgement

  • Russian Foundation for Basic Research, Project 17-04-02039 (environmental analysis)

  • Russian Geographical Society (funds for this travel)

    []{style="display: none;"}

  • WWF Russia (spatial data management for PAMPAN project)

  • John Bengtson, Vladimir Chernoook (approval for participations)

  • AMSS-2020 and 26MMWG participants and observers, welcoming Anchorage and Alaska.

Anderson M, Drobot S, Bliss AC. 2019. Snow Melt Onset Over Arctic Sea Ice from SMMR and SSM/I-SSMIS Brightness Temperatures, Version 4. Boulder, Colorado USA: NASA National Snow and Ice Data Center Distributed Active Archive Center. 10.5067/A9YK15H5EBHK.

Belchansky GI, Douglas DC, Mordvintsev IN, Platonov NG. 2004. Estimating the time of melt onset, melt duration and freeze onset over Arctic sea-ice area using active and passive microwave data. Remote Sensing of Environment, 92(1): 21–39. 10.1016/j.rse.2004.05.001.

Drobot SD, Anderson MR. 2001. An improved method for determining snowmelt onset dates over Arctic sea ice using scanning multichannel microwave radiometer and Special Sensor Microwave/Imager data. J Geophys Res, 106: 24, 033–24, 049. 10.1029/2000JD000171.

Kelly BP, Mordvintsev IN, Nghiem S, Boveng P. 2010. Developing a pan Arctic protocol for monitoring seal habitat. In: Marine Mammals of the Holarctic: Collection of Scientific Papers after the Sixth International Conference (Kaliningrad, Russia, October 11–15, 2010). Калиниград: Капрос., pp. 445–450. 978-5-904291-05-1.

Lavielle M. 1999. Detection of multiple changes in a sequence of dependent variables. Stochastic Processes and their Applications, 83(1): 79–102. 10.1016/S0304-4149(99)00023-X.

Lavielle M. 2005. Using penalized contrasts for the change-point problem. Institut national de recherche en informatique et en automatique.

Markus T, Miller J. 2019 (06 December). Arctic sea ice melt. NASA Goddard Space Flight Center’s Cryospheric Sciences Laboratory. https://earth.gsfc.nasa.gov/cryo/data/arctic-sea-ice-melt (accessed 06 January 2020).

Markus T, Stroeve JC, Miller J. 2009. Recent changes in Arctic sea ice melt onset, freezeup, and melt season length. Journal of Geophysical Research: Oceans, 114(C12). American Geophysical Union (AGU). C12024. 10.1029/2009JC005436.

Mordvintsev IN, Platonov NG, Alpatsky IV. 2011. Arctic sea ice long-term dynamics according to the satellite microwave data. Izvestiya, Atmospheric and Oceanic Physics, 47(9): 1127–1134. Pleiades Publishing Ltd. 10.1134/s0001433811090106.